Imagen de Portada

Back To The Future: A Hybrid Transformer-XGBoost Model for Action-oriented Future-proofing Nowcasting

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Sun, Ziheng
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

FusionCast: Enhancing Precipitation Nowcasting with Asymmetric Cross-Modal Fusion and Future Radar Priors
por: Wang, Henan, et al.
Publicado: (2026)

Extreme Precipitation Nowcasting using Transformer-based Generative Models
por: Meo, Cristian, et al.
Publicado: (2024)

Back to the Future: GNN-based NO$_2$ Forecasting via Future Covariates
por: Giganti, Antonio, et al.
Publicado: (2024)

Back to the Future: Look-ahead Augmentation and Parallel Self-Refinement for Time Series Forecasting
por: Kim, Sunho, et al.
Publicado: (2026)

Precipitation Nowcasting Using Physics Informed Discriminator Generative Models
por: Yin, Junzhe, et al.
Publicado: (2024)

Traffic flow forecasting, STL decomposition, Hybrid model, LSTM, ARIMA, XGBoost, Intelligent transportation systems
por: Yuan, Fujiang, et al.
Publicado: (2025)

Accelerating Training with Neuron Interaction and Nowcasting Networks
por: Knyazev, Boris, et al.
Publicado: (2024)

Stable Attention Response for Reliable Precipitation Nowcasting
por: Wen, Penghui, et al.
Publicado: (2026)

Spatio-Temporal Trajectory Foundation Model - Recent Advances and Future Directions
por: Yang, Sean Bin, et al.
Publicado: (2025)

CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
por: Gong, Junchao, et al.
Publicado: (2024)

Bridging Dynamic Factor Models and Neural Controlled Differential Equations for Nowcasting GDP
por: Lim, Seonkyu, et al.
Publicado: (2024)

Dynamic Meta-Learning for Adaptive XGBoost-Neural Ensembles
por: Sedek, Arthur
Publicado: (2025)

How Effective Are Time-Series Models for Precipitation Nowcasting? A Comprehensive Benchmark for GNSS-based Precipitation Nowcasting
por: Zhang, Yifang, et al.
Publicado: (2025)

Medical Multimodal Foundation Models in Clinical Diagnosis and Treatment: Applications, Challenges, and Future Directions
por: Sun, Kai, et al.
Publicado: (2024)

Precipitation Nowcasting Using Diffusion Transformer with Causal Attention
por: Li, ChaoRong, et al.
Publicado: (2024)

FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction
por: Zeng, Zhiyuan, et al.
Publicado: (2025)

Transforming Multimodal Models into Action Models for Radiotherapy
por: Ferrante, Matteo, et al.
Publicado: (2025)

On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation
por: Zhang, Yuheng, et al.
Publicado: (2024)

Explaining an Agent's Future Beliefs through Temporally Decomposing Future Reward Estimators
por: Towers, Mark, et al.
Publicado: (2024)

TF-CoDiT: Conditional Time Series Synthesis with Diffusion Transformers for Treasury Futures
por: Zhang, Yingxiao, et al.
Publicado: (2026)

Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN
por: Yu, Chang, et al.
Publicado: (2024)

Beyond MSE: Improving Precipitation Nowcasting with Multi-Quantile Regression
por: van Nieuwkoop, Gijs, et al.
Publicado: (2026)

PIANO: Physics-informed Dual Neural Operator for Precipitation Nowcasting
por: Chin, Seokhyun, et al.
Publicado: (2025)

Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors
por: Qin, Yuze, et al.
Publicado: (2026)

Predicting the Future by Retrieving the Past
por: Du, Dazhao, et al.
Publicado: (2025)

Personalized Student Knowledge Modeling for Future Learning Resource Prediction
por: Hashemifar, Soroush, et al.
Publicado: (2025)

Forecasting the Future with Future Technologies: Advancements in Large Meteorological Models
por: Shu, Hailong, et al.
Publicado: (2024)

RainBalance: Alleviating Dual Imbalance in GNSS-based Precipitation Nowcasting via Continuous Probability Modeling
por: Zhang, Yifang, et al.
Publicado: (2026)

A Kriging-Random Forest Hybrid Model for Real-time Ground Property Prediction during Earth Pressure Balance Shield Tunneling
por: Geng, Ziheng, et al.
Publicado: (2023)

MAD-SmaAt-GNet: A Multimodal Advection-Guided Neural Network for Precipitation Nowcasting
por: van Wonderen, Samuel, et al.
Publicado: (2026)

SmaAT-QMix-UNet: A Parameter-Efficient Vector-Quantized UNet for Precipitation Nowcasting
por: Stavrou, Nikolas, et al.
Publicado: (2026)

Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
por: Li, Fang, et al.
Publicado: (2023)

Looping Back to Move Forward: Recursive Transformers for Efficient and Flexible Large Multimodal Models
por: Xu, Ruihan, et al.
Publicado: (2026)

Estimating oil recovery factor using machine learning: Applications of XGBoost classification
por: Roustazadeh, Alireza, et al.
Publicado: (2022)

K-means Derived Unsupervised Feature Selection using Improved ADMM
por: Sun, Ziheng, et al.
Publicado: (2024)

Graph Prompting for Graph Learning Models: Recent Advances and Future Directions
por: Fu, Xingbo, et al.
Publicado: (2025)

The Future of Continual Learning in the Era of Foundation Models: Three Key Directions
por: Bell, Jack, et al.
Publicado: (2025)

Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
por: Hu, Yifan, et al.
Publicado: (2025)

A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions
por: Shi, Jie, et al.
Publicado: (2026)

Recurrent Action Transformer with Memory
por: Cherepanov, Egor, et al.
Publicado: (2023)